How Quality Data Saves Money

Several weeks ago, a customer called because she thought that one of her vocational center workers may be getting shorted on his paycheck. He wasn’t technically an employee; the worker resided at a group home and worked days at a vocational center for persons with intellectual disabilities.

It turned out that even though the software used to manage pay rates for workers did data validation on the client, someone had updated several of the rates directly at the database table, bypassing business rules dictating a minimum wage and piece rate calculations/validation.

Bad Data Costs Money

Samuel, the underpaid worker, was very happy to receive almost a year’s worth of back pay, but for the vocational center, the mistake was costly. Employee hours were spent tracking down and fixing the bad data. Once the bad data was located, even more time went into processing back pay, reconciling payroll and correcting related accounting details, which meant more payable employee hours worked. The combination of these unbudgeted, unexpected expenses placed a burden on the already trim, non-profit workshop.

Bad Data Costs Reputation

Notifying the worker’s guardian of the error tarnished the shop’s solid image. Unfortunately for the vocational center, Samuel’s guardian misunderstood the initial contact regarding the pay error, thinking that the shop was placing the blame on Samuel. The irate guardian then called the vocational center and proceeded to chastise and criticize the shop supervisor and employees for what he perceived to be ineptitude and incompetence. Contributing to the snowball effect, the underpaid, overworked supervisor hung up on the guardian once the verbal insults began. Then the guardian went so far as to contact the local news station to complain. Luckily, the guardian called the vocational center to warn them of the approaching storm of reporters. The center’s director soon learned of the mess, so she called the guardian and was able to explain what had happened, and that it was never any fault of Samuel’s. The guardian agreed to update the local news on the situation and keep Samuel in vocational services, but insisted on collecting interest on the back pay for his ward. The vocational center agreed to pay the interest.

Bad Data Costs Time

Meetings were held about how to prevent that kind of error going forward. The team decided to spend some resources on investigating whether all of their data was valid. After several weeks, their “Valid Data Only” project had cleaned up many of the shop’s database records while also improving processes and checks to help prevent future data errors.

Bad Data Gets In

Many companies work with data sets from external sources that frequently require custom integration, and “behind-the-scenes” loading of data. While it is not uncommon for users to be the source of bad data, the requirements involved with using external data can also be to blame. A variation in process allows unconventional data integration and loading to completely bypass existing data validation checks in the client applications which can result in invalid/bad data, unnecessary expenses, and even serious damage to the company.

It doesn’t have to be so. By employing a process of continual monitoring of your data for errors, you can stay ahead of potential problems, often mitigating them completely, before they negatively impact your business.